Survey of research on abnormal traffic detection for software defined networks
Since software defined network (SDN) was more vulnerable to network attacks than traditional networks, the research progress of abnormal traffic detection for software defined network in recent years from the technical principle and architecture characteristics was summarized, the possible organizat...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2024-03-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024016/ |
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| _version_ | 1841540036123688960 |
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| author | Yu FU Kun WANG Xueyuan DUAN Taotao LIU |
| author_facet | Yu FU Kun WANG Xueyuan DUAN Taotao LIU |
| author_sort | Yu FU |
| collection | DOAJ |
| description | Since software defined network (SDN) was more vulnerable to network attacks than traditional networks, the research progress of abnormal traffic detection for software defined network in recent years from the technical principle and architecture characteristics was summarized, the possible organizational forms of network attacks on SDN were analyzed, and the characteristics, advantages, and disadvantages of current technologies related to abnormal traffic detection, abnormal traffic traceability, and abnormal traffic mitigation were discussed.The data sets commonly used in current research were compared and analyzed, and some general data preprocessing methods were sorted out.The research direction of abnormal traffic detection methods in the SDN environment in the future was summarized and prospected.The research results can guide the selection of adaptation methods in practical application requirements, and the problems and contradictions to be solved can guide subsequent research. |
| format | Article |
| id | doaj-art-434e014e25b64a6a8f2f3941ef410534 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2024-03-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-434e014e25b64a6a8f2f3941ef4105342025-01-14T06:21:58ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2024-03-014520822659296816Survey of research on abnormal traffic detection for software defined networksYu FUKun WANGXueyuan DUANTaotao LIUSince software defined network (SDN) was more vulnerable to network attacks than traditional networks, the research progress of abnormal traffic detection for software defined network in recent years from the technical principle and architecture characteristics was summarized, the possible organizational forms of network attacks on SDN were analyzed, and the characteristics, advantages, and disadvantages of current technologies related to abnormal traffic detection, abnormal traffic traceability, and abnormal traffic mitigation were discussed.The data sets commonly used in current research were compared and analyzed, and some general data preprocessing methods were sorted out.The research direction of abnormal traffic detection methods in the SDN environment in the future was summarized and prospected.The research results can guide the selection of adaptation methods in practical application requirements, and the problems and contradictions to be solved can guide subsequent research.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024016/software defined networkdeep learningabnormal traffic detection,abnormal traffic traceabilityabnormal traffic mitigation |
| spellingShingle | Yu FU Kun WANG Xueyuan DUAN Taotao LIU Survey of research on abnormal traffic detection for software defined networks Tongxin xuebao software defined network deep learning abnormal traffic detection, abnormal traffic traceability abnormal traffic mitigation |
| title | Survey of research on abnormal traffic detection for software defined networks |
| title_full | Survey of research on abnormal traffic detection for software defined networks |
| title_fullStr | Survey of research on abnormal traffic detection for software defined networks |
| title_full_unstemmed | Survey of research on abnormal traffic detection for software defined networks |
| title_short | Survey of research on abnormal traffic detection for software defined networks |
| title_sort | survey of research on abnormal traffic detection for software defined networks |
| topic | software defined network deep learning abnormal traffic detection, abnormal traffic traceability abnormal traffic mitigation |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024016/ |
| work_keys_str_mv | AT yufu surveyofresearchonabnormaltrafficdetectionforsoftwaredefinednetworks AT kunwang surveyofresearchonabnormaltrafficdetectionforsoftwaredefinednetworks AT xueyuanduan surveyofresearchonabnormaltrafficdetectionforsoftwaredefinednetworks AT taotaoliu surveyofresearchonabnormaltrafficdetectionforsoftwaredefinednetworks |